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Hadziqul Abror
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Program Studi Teknik Perminyakan, Fakultas Teknik, Universitas Jember Jl. Kalimantan Tegalboto No.37, Krajan Timur, Sumbersari, Kec. Sumbersari, Kabupaten Jember, Jawa Timur 68121.
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Journal of Sustainable Energy Development
Published by Universitas Jember
ISSN : -     EISSN : 30482585     DOI : -
Core Subject : Science, Engineering,
Energy Engineering
The Journal of Sustainable Energy Development is the official scientific journal of Petroleum Engineering, Faculty of Engineering, University of Jember for the dissemination of information on research activities, technology engineering development and laboratory testing in sustainable energy development. The focus and scope of JSED as follows: Oil and Gas Technology: Production, Reservoir, and Drilling Technology, Enhance Oil Recovery Geothermal Technology: Reservoir Characterization and Modeling, Development of Productivity-Enhancing Methods, Plan of Vevelopment Earth Science: Geology, Geophysics, Geochemical Renewable Energy: Wind energy, Hydro energy, Solar cell energy, Biomass
Arjuna Subject : Energi (semua kategori) - Energi Terbarukan, Keberlanjutan dan Lingkungan
Articles 6 Documents
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Search results for , issue "Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)" : 6 Documents clear
Estimasi Cadangan Lapangan RTD Menggunakan Metode Decline Curve Analysis Dan Log WC Vs Np Maulana, Nadhif; Abror, Hadziqul; welayaturromadhona
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

Lapangan RTD dibor pada tahun 1984 dengan sumur RTD-1 dan terus berproduksi sejak saat itu. Hingga tahun 2020, total sumur yang dibor di lapangan sebanyak 20 sumur, 13 diantaranya masih berproduksi dan 6 sumur digunakan untuk injeksi air. Lapangan RTD terdiri dari 3 reservoir yaitu Holland Greensand, De Lier Sandstone, dan Ijsselmonde Sandstone. Ketiga reservoir Rotterdam menghasilkan minyak, air dan sejumlah kecil gas. Reservoir Batupasir IJsselmonde telah berproduksi sejak tahun 1984, Reservoir Batupasir De Lier telah berproduksi sejak tahun 1986 dan Reservoir Holland Greensand telah berproduksi sejak tahun 1988. Penelitian ini membahas tentang evaluasi cadangan pada lapangan RTD dengan melakukan perhitungan cadangan. Metode yang digunakan adalah metode Decline Curve Analysis dan metode Log WC vs Np. Perhitungan akan dikelompokkan menjadi 2 yaitu seluruh lapangan RTD dengan menggunakan kedua metode dan yang kedua yaitu menggunakan metode Log WC vs Np pada masing-masing lapisan. Metode penelitian yang digunakan adalah study literatur yang berhubungan dengan perhitungan cadangan pada lapangan RTD yaitu dengan mengumpulkan informasi data sekunder mengenai data – data untuk forecasting dalam bentuk buku – buku literatur, jurnal, dan tugas akhir yang berkaitan dengan judul peneliti. Lapangan RTD memiliki total STOOIP 319 MMSTB dari 3 reservoir dan masing-masing reservoir memiliki watercut 56% - 82%. Perhitungan cadangan Lapangan RTD mendapatkan hasil RR 8,71 MMSTB dengan EUR 67,52 MMSTB, dan memperoleh hasil RR 8,25 MMSTB dengan EUR 67,05 MMSTB. Hasil masing-masing lapisan di lapangan RTD bila ditotal mendapatkan hasil RR 6,62 MMSTB dengan EUR 65,43 MMSTB.
Desain Hydraulic Fracturing Sebagai upaya Peningkatan Produktivitas Sumur X Lapangan Y Berliana Dewi, Salsabila; Abror, Hadziqul; welayaturromadhona, welayaturromadhona
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

The decline in oil production due to aging wells and formation damage has become a critical challenge in the petroleum industry. This study focuses on the design of hydraulic fracturing to improve Well X's productivity in the Telisa Formation, Central Sumatra Basin. The research utilized FracCADE 7.0 software to simulate hydraulic fracturing scenarios and optimize fracture geometry and conductivity. The parameters investigated included variations in fracturing fluid volume, proppant types, and injection methods, culminating in 12 simulation scenarios. The geomechanical analysis revealed that the Telisa Formation, dominated by low Young’s modulus (<3×10⁶ psi) and low Poisson’s ratio, is favorable for fracturing, as it tends to generate wider fractures at lower pumping pressures. However, higher Young's modulus layers at greater depths showed the potential for longer but narrower fractures, albeit requiring higher pumping pressures. These characteristics guided the selection of fracturing intervals and operational parameters to optimize stimulation results. The results showed that the optimal scenario utilized 32,239 gallons of fracturing fluid, Brady Sand as the proppant, and the Proppant Concentration Step-Wise Increasing (PCSI) injection method. This configuration produced fractures with a half-length of 171 ft, width of 0.149 inches, height of 253.3 ft, and fracture conductivity of 13,592 mD.ft, resulting in a Fold of Increase (FOI) of 6.82. Economically, this scenario required a total cost of $574,576.47 and achieved a pay-out time (POT) of 48 days, with a net present value (NPV) of $3,534,073.21 after one year. This research highlights the technical and economic advantages of hydraulic fracturing in maximizing well productivity. It provides a detailed recommendation for future stimulation activities in Well X, emphasizing the balance between production enhancement and cost efficiency.
Analisis Kinerja Produksi Sumur LX Menggunakan Artificial Lift PCP dan SRP Serta Pendekatan Keekonomian Gunawan, Benny; Eklezia Dwi Saputri, Eriska; Triono, Agus
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

In the oil industry, the main challenge is to maintain a stable oil production rate, especially when reservoir pressure decreases. Therefore, artificial lift methods are used to increase production rates. The LX well is one of the wells located in the Tarakan field, North Kalimantan, where at the beginning of production the Artificial Lift method had not been used. This study aims to analyze the production performance and economic aspects of the use of 2 artificial lift methods, namely Progressive Cavity Pump (PCP) and Sucker Rod Pump (SRP). The simulation results show that the flow rate increases with increasing operating speed and number of strokes per minute. The optimal speed for PCP is 400 rpm with a flow rate of 1668.14 STB/d, while for SRP, the optimal SPM is 22 with a flow rate of 1686.89 STB/d. The analysis of the economic calculation of the use of the PCP artificial lift method obtained a POT of 0.69 years. Calculation with DCA method, obtained IRR ranging from 132% - 133% and NPV ranging from $3,499,432 - $3,842,340. Based on the results of economic calculations from the use of the SRP artificial lifting method, the POT is 1 year. Calculation with the DCA method obtained IRR values ranging from 82% - 84% and NPV ranging from $1,661,827 - $2,008,573. These results indicate that this project is financially feasible.
Optimasi Produksi Menggunakan Injeksi CO2 dan Penerapan Sistem Carbon Pricing Reservoir X Wulan, Nanda; Eklezia Dwi Saputri, Eriska; Laksmita Sari, Riska
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

Indonesia tercatat sebagai salah satu negara penyumbang emisi gas CO₂ terbesar di dunia dengan total emisi mencapai 1,3 Gt di mana 50,6% berasal dari sektor industri migas. Oleh karena itu, Pemerintah Indonesia berkomitmen untuk menurunkan emisi GRK sebesar 29%. Penelitian ini bertujuan untuk mengurangi emisi GRK dengan menerapkan sistem carbon pricing pada perhitungan keekonomian dan penggunaan metode injeksi gas CO2 pada reservoir X. Selain itu, metode injeksi CO2 diharapkan nantinya dapat mengoptimalkan produksi minyak pada reservoir. Injeksi CO₂ di reservoir X dan penerapan sistem carbon pricing menggunakan skema Production Sharing Contract (PSC) Gross Split dirancang dengan data asumsi yang memiliki karakteristik minyak ringan (°API 35) dan batuan sandstone dengan kedalaman 10.000 ft. Pada awal produksi, reservoir X mengalami penurunan yang signifikan akibat aquifer support yang lemah, sehingga diterapkan Enhanced Oil Recovery (EOR) dengan injeksi CO₂ secara miscible dan immiscible. Penelitian ini menggunakan 3 skenario yang nantinya disimulasikan dan dibandingkan hasil perolehan terbaik. Skenario 3 merupakan skenario terbaik dengan menginjeksikan 1 sumur produksi dan 2 sumur injeksi yang menunjukkan peningkatan kumulatif produksi minyak lebih besar dari simulasi basecase, diperoleh nilai sebesar 7,6 MMBBL dengan recovery factor sebesar 55% dan penurunan water cut hingga 91%. Selain itu, hasil perhitungan keekonomian dengan menerapkan sistem carbon pricing menghasilkan NPV sebesar 786.678,21 USD, IRR sebesar 11%, dan Pay Out Time (POT) selama 7,4 bulan yang mengindikasikan kelayakan ekonomi proyek bagi kontraktor. Penelitian ini memberikan triple-win solution dengan meningkatkan produksi minyak, mendukung target nasional pengurangan emisi karbon, dan memberikan keuntungan ekonomi.
Studi Simulasi: Pengaruh Soaking Time dan Injection rate Terhadap Peningkatan Recovery Factor dalam Injeksi CO2 Huff & Puff Pada Sumur X Sahtria panjaitan, sahtria panjaitan; Triono, Agus; Eklezia Dwi Saputri, Eriska
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

CO₂ Huff & Puff injection is an effective enhanced oil recovery (EOR) method to boost production in declining reservoirs. This study focuses on simulating CO₂ Huff & Puff injection in Well X, SKW Field, by analyzing injection parameters such as soaking duration and injection rate. The simulation was conducted without history matching but included sensitivity analysis to evaluate reservoir performance. Seven soaking time variations (5–35 days) were tested, with 20 days yielding the highest Recovery Factor (RF) of 4.064%. Injection rate variations ranged from 1×10⁶ to 1.6×10⁶ ft³/day, with 1.4×10⁶ ft³/day achieving the highest RF increase of 4.070%. Soaking time and injection rate significantly impact oil recovery; however, excessive soaking leads to gravity segregation, reducing oil displacement efficiency. The optimal combination for maximizing recovery in Well X is a 20-day soaking time with a CO₂ injection rate of 1.4×10⁶ ft³/day. Keywords: CO2 Injection; Huff &Puff, Soaking Time, Injection rate
Studi Prediksi Porositas Dengan Menggunakan Metode Deterministik dan Machine Learning Pada Lapangan “X” Hafwandi, Babas Samudera
Journal of Sustainable Energy Development Vol. 3 No. 1 (2025): Journal of Sustainable Energy Development (JSED)
Publisher : Petroleum Engineering, Faculty of Engineering, University of Jember

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Abstract

Porosity is one of the most critical parameters in reservoir characterization, as it directly influences hydrocarbon storage capacity. Accurate porosity prediction becomes even more essential in fields with limited core data, such as Field “X”, located in the South Sumatra Basin. This study compares two different porosity prediction approaches: a deterministic method based on well log interpretation using NPHI and RHOB logs, and various Machine Learning (ML) algorithms, including Random Forest (RF), K-Nearest Neighbor (KNN), Gradient Boosting (GBR), AdaBoost (ADA), Support Vector Machine (SVM), and Decision Tree (DT). Data preprocessing involved feature selection using Pearson, Spearman, and Kendall correlation coefficients to identify the most influential log parameters. The dataset was then divided into training (70%) and testing (30%) subsets. Model performance was evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The deterministic method yielded an MAE of 0.0658 and RMSE of 0.0906, while the best ML model, Random Forest, achieved an MAE of 0.0329 and RMSE of 0.0434 on the testing dataset. In conclusion, Machine Learning, especially the Random Forest model, proves to be a more reliable and accurate tool for porosity prediction in geologically complex fields, offering significant potential for enhancing reservoir modeling and field development planning.

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